Sexually Dimorphic Gene Expression Associated with Growth and Reproduction of Tongue Sole (Cynoglossus Semilaevis) Revealed by Brain Transcriptome Analysis

International Journal of Molecular Sciences

Article Sexually Dimorphic Gene Expression Associated with Growth and Reproduction of Tongue Sole (Cynoglossus semilaevis) Revealed by Brain Transcriptome Analysis

Pingping Wang 1,†, Min Zheng 1,2,†, Jian Liu 3, Yongzhuang Liu 3, Jianguo Lu 1,* and Xiaowen Sun 1

1 Heilongjiang River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Harbin 150070, China; [email protected] (P.W.); [email protected] (M.Z.); [email protected] (X.S.) 2 Environmental Engineering Program, Department of Civil Engineering, Auburn University, Auburn, AL 36849, USA 3 School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China; [email protected] (J.L.); [email protected] (Y.L.) * Correspondence: [email protected]; Tel.: +86-451-8486-1322 † These authors contributed equally to this work.

Academic Editors: Jun Li and Li Lin Received: 25 March 2016; Accepted: 19 August 2016; Published: 26 August 2016

Abstract: In this study, we performed a comprehensive analysis of the transcriptome of one- and two-year-old male and female brains of Cynoglossus semilaevis by high-throughput Illumina sequencing. A total of 77,066 transcripts, corresponding to 21,475 unigenes, were obtained with a N50 value of 4349 bp. Of these unigenes, 33 genes were found to have significant differential expression and potentially associated with growth, from which 18 genes were down-regulated and 12 genes were up-regulated in two-year-old males, most of these genes had no significant differences in expression among one-year-old males and females and two-year-old females. A similar analysis was conducted to look for genes associated with reproduction; 25 genes were identified, among them, five genes were found to be down regulated and 20 genes up regulated in two-year-old males, again, most of the genes had no significant expression differences among the other three. The performance of up regulated genes in Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was significantly different between two-year-old males and females. Males had a high gene expression in genetic information processing, while female’s highly expressed genes were mainly enriched on organismal systems. Our work identified a set of sex-biased genes potentially associated with growth and reproduction that might be the candidate factors affecting sexual dimorphism of tongue sole, laying the foundation to understand the complex process of sex determination of this economic valuable species.

Keywords: sexually dimorphic; tongue sole; transcriptome analysis

1. Introduction Tongue sole (Cynoglossus semilaevis) is a valuable marine ﬁsh in China, which is receiving more attention because of its good taste and nutritional value. However, the species is decreasing in number in the wild despite increasing market demand, which favors more production of the species [1]. Apart from its increasing economic value, it also has an intriguing reproductive biology. Genetically, tongue sole has ZW sex-determination system [2]. Males are the homogametic sex (ZZ), while females are the heterogametic sex (ZW). Male and female tongue sole are considerably different in size and

Int. J. Mol. Sci. 2016, 17, 1402; doi:10.3390/ijms17091402 www.mdpi.com/journal/ijms Int. J. Mol. Sci. 2016, 17, 1402 2 of 17 growth rate: mature females are twice larger in length and six times greater in weight than their male counterparts [3]. Thus, understanding the underpinning of sexual dimorphism and sex determination in this species is essential for developing methods to boost its productivity to meet the aquaculture market demands. Although sexual determination in some fish is partly determined by the environment [4–6], brain is still a major organ involved in fish growth and reproduction [7], and plays a key role in sexual dimorphism and sex determination, including the regulation of reproduction, maturation and sexual behavior in both sexes. The influence of brain on development is mainly mediated by the Brain–Pituitary–Gonadal (BPG) axis [8]. Gahr [9] found that male quail transplanted with female forebrain do not develop normal testes, indicating that a male brain is necessary for normal testes development. This demonstrates that sexual dimorphism in brain is not entirely determined by hormones secreted by the gonads, and brain develops differently between sexes even before the gonad development [10–12]. Therefore, understanding the mechanism of sexual dimorphism in brain is fundamental for enhancing our knowledge of development processes and exploring the genetic toolkit to maintain or change the difference between sexes. Yang and colleagues [13] found that relatively small changes in gene expression might control functional sexual dimorphism in the brain, suggesting that differences in a few of those genes may become biological significant when interact with other genes in functional gene networks. Thus, uncovering the sex-biased genes are thought to be necessary when studying the mechanism of sexual dimorphism, and these genes may evolve differently under selection pressure, in turn, acting on the sexual phenotype [14]. For researchers, the major challenge is to explain the huge list of differentially expressed genes (DEGs) under certain conditions. A decade ago, automatic functional classification method using Gene Ontology (GO) was proposed to help study the function of these DEGs [15]. The first step is to group the list of DEGs into functional groups, which can offer insight into the biological mechanisms at the given condition. In addition, a well-characterized transcriptome is considered to be helpful to identify functional genes underlying the certain phenotypic variation in several ways. Gonads, as the main sex organ, are often utilized to get a comprehensive overview of differentially expressed genes responsible for sexual dimorphism. Up to now, thousands of sex-biased genes have been identified from gonads in many species, including fruit fly [16], mouse [17] and some teleost, such as zebrafish [18], Nile tilapia [19], sharpsnout seabream [20], guppy [21], and yellow catfish [22]. However, sex-biased genes expressed in brain have been less well studied. For the sexually dimorphic development of tongue sole, studies have mainly focused on the hormones expressed in brain known to influence the BPG-axis such as pituitary adenylate cyclase-activating polypeptide (PACAP) [23,24], growth hormone-releasing hormone (GHRH) [23,24] and growth hormone (GH) [25,26]. However, few studies have been published at the transcriptomic level to identify and characterize sex-biased genes related to growth and reproduction in tongue sole brain. Recently, the whole genome of tongue sole was published [2], enabling whole genome-based transcriptomic analyses. In this study, we seek to identify the molecular mechanism underlying sexual dimorphism of the brain transcriptome of tongue sole. Fish used for this project were one- and two-year-old tongue sole. The average body weights of one-year-old male and female were 54 and 99 g, and the average body lengths were 21 and 25 cm, respectively. For two-year-old fish, the average weights were 337 and 1380 g, and average lengths were 27 and 42 cm, for male and female respectively. Females were much bigger than males. Two-year-old females were still immature, while males were mature. We used the RNA-Sequencing approach [27] aimed at identifying the differentially expressed genes of tongue sole. Brain transcriptomic profiles of one- and two-year-old males and females were analyzed and revealed a number of sexually differentially expressed genes potentially associated with growth and reproduction. These data will hopefully provide a useful genetic resource for further sex determination studies on tongue sole. Int. J. Mol. Sci. 2016, 17, 1402 3 of 17 Int. J. Mol. Sci. 2016, 17, 1402 3 of 17

2. Results Results

2.1. Transcriptome Transcriptome Sequencing and Assembly To obtain comprehensive information of gene expression between sexes, we sequenced four transcriptomes derived derived from from female female and and male male brains brains at at one and two-year-old tongue sole by using Illumina Hiseq2000Hiseq2000 technology. technology. A A workﬂow workflow with with the transcriptomethe transcriptome data analysisdata analysis procedures procedures is shown is shownin Figure in1 Figure. 1.

FigureFigure 1. 1. Work-flowWork-ﬂow of the transcriptome analysis of tongue sole.

In total, 201,822,072 paired-end reads were generated, encompassing 20.2 Gb of sequence. Low In total, 201,822,072 paired-end reads were generated, encompassing 20.2 Gb of sequence. quality reads and reads with ambiguous nucleotides were discarded, leaving 191,631,250 clean reads forLow transcriptome quality reads assembly and reads and with analysis. ambiguous To nucleotidesassess our transcriptome were discarded, assembly, leaving 191,631,250we mapped clean our cleanreads paired-end for transcriptome reads to assembly the C. semilaevis and analysis. whole To genome. assess ourApproximately transcriptome 84.2% assembly, of them we exhibited mapped C. semilaevis significantour clean paired-endhits to the readsgenome. to the These reads werewhole assembled genome. into Approximately 77,066 transcripts 84.2% in of themtotal, correspondingexhibited significant to 21,475 hits unigenes, to the genome. with an These averag readse length were of assembled 3059 bp, intothe N50 77,066 value transcripts of 4349 inbp total,and thecorresponding N90 value of to 1638 21,475 bp. unigenes, Transcriptome with an data average obtained length from of 3059four sa bp,mples the N50 has valuebeen uploaded of 4349 bp to and NCBI the SRAN90 valuesite, ofwith 1638 accession bp. Transcriptome numbers dataof SRR2046 obtained146, from SRR2046147, four samples SRR2046153, has been uploaded and SRR2046154, to NCBI SRA respectively.site, with accession numbers of SRR2046146, SRR2046147, SRR2046153, and SRR2046154, respectively. 2.2. Gene Identification and Functional Annotation 2.2. Gene Identification and Functional Annotation All transcribed genes were functionally annotated by blasting the NCBI non-redundant database. All transcribed genes were functionally annotated by blasting the NCBI non-redundant A total of 10,185 genes were annotated with at least one significant hit (E value < 1 × 10−5). Of these database. A total of 10,185 genes were annotated with at least one significant hit (E value < 1 × 10−5). genes, 5467 genes were further annotated by Gene Ontology (GO) with 5845 GO terms. A histogram of Of these genes, 5467 genes were further annotated by Gene Ontology (GO) with 5845 GO terms. A the number and percent of genes falling into the GO categories is given in Figure S1. The category of histogram of the number and percent of genes falling into the GO categories is given in Figure S1. biological process contained the most genes, followed by molecular function and cellular component. The category of biological process contained the most genes, followed by molecular function and Briefly, in biological process, cellular processes and metabolic processes were the most represented cellular component. Briefly, in biological process, cellular processes and metabolic processes were the most represented categories; with a total of 3553 genes assigned to cellular process (GO: 0009987,

Int. J. Mol. Sci. 2016, 17, 1402 4 of 17 Int. J. Mol. Sci. 2016, 17, 1402 4 of 17 categories;64.6%) and with 2756 a totalgenes of to 3553 metabolic genes assigned process to (GO: cellular 0008152, process 50.2%). (GO: 0009987,In the category 64.6%) and with 2756 cellular genes tocomponent, metabolic cell process (GO: (GO: 0005623, 0008152, 59.2%) 50.2%). and Inorganelle the category (GO: with0043226, cellular 30.5%) component, were annotated cell (GO: with 0005623, most 59.2%)abundant and genes. organelle Finally, (GO: in 0043226, the category 30.5%) of were molecu annotatedlar functions, with most binding abundant and catalytic genes. Finally,activityin were the categorytwo most of frequent molecular classes. functions, binding and catalytic activity were two most frequent classes. Functional pathway analysis based on the KyotoKyoto Encyclopedia of Genes and Genomes (KEGG) database was also conducted as aa complementarycomplementary approach to categorizecategorize andand annotateannotate transcribedtranscribed genes. Of Of the the 21,475 21,475 transcribed genes, genes, 7879 7879 gene geness were assigned to KEGG orthologs, and then categorized into six functional groups (Table S1A).S1A). InIn short,short, ofof the genes with KEGG annotation, 1929 genes (22.5%)(22.5%) werewere assigned assigned to to metabolism, metabolism, 1394 1394 (17.7%) (17.7%) to geneticto genetic information information processing, processing, and 2774and genes2774 genes (35.2%) (35.2%) were classiﬁed were classified to environmental to environm informationental information processing. processing. Cellular processes, Cellular organismalprocesses, systemsorganismal and systems human diseasesand human contained diseases 1883 containe (23.8%),d 2944 1883 (37.3%), (23.8%), and 2944 2695 (37.3%), (34.2%) and KEGG 2695 annotated (34.2%) genes,KEGG respectively.annotated genes, respectively.

2.3. Differentially Expressed Genes (DEGs)(DEGs) and GeneGene EnrichmentEnrichment AnalysisAnalysis Gene expression profilingprofiling of thethe malemale vs.vs. female brain at two developmental stages are plotted in FigureFigure2 2.. FromFrom thethe totaltotal ofof 21,47521,475 transcribedtranscribed genes,genes, 771771 genesgenes werewere foundfound toto havehave sex-specificsex-specific expression pattern in one-year-old fish,fish, 469469 of them were up-regulated inin the male and the rest in the female. For the two-year-old fish, fish, the number of DEGs (5498 genes) was about seven times greater than that in one-year-old fish.fish. Among those DEGs, 3025 genes were found to be be up-regulated up-regulated in in male, male, and thethe restrest inin female.female. MoreMore up-regulatedup-regulated genes genes were were found found in in M2 M2 than than F2, F2, which which might might be be related related to theto the maturation maturation of malesof males in thisin this stage. stage. Overall, Overall, co-expressed co-expressed genes genes (CEGs) (CEGs) still still made made up up the the majority majority of allof all genes genes at at both both developmental developmental stages. stages. Transcriptome Transcriptome profiling profiling and and differentiallydifferentially expressedexpressed genes were listedlisted in supplementary TableTable S2.S2. DEGs,DEGs, CEGs and NEGs between male and female tongue sole were shownshown inin supplementarysupplementary TableTable S4.S4.

Figure 2.2. Gene expression profiling proﬁling in brain tissue between male and female tongue sole at two developmental stages. Non-expressed genes (NEGs) marked as black dots.dots. Differentially expressed genes (DEGs) marked as dark blue and light blue dots. Co-expressed genes (CEGs)(CEGs) marked as red dots.

Gene enrichment analysis was conducted to further understand the biological functions of the Gene enrichment analysis was conducted to further understand the biological functions of the DEGs. All DEGs were mapped to the terms of Gene Ontology and compared with the background of DEGs. All DEGs were mapped to the terms of Gene Ontology and compared with the background of the whole transcriptome (Table 1). More DEGs in two-year-old fish were identified (711 up-regulated the whole transcriptome (Table1). More DEGs in two-year-old fish were identified (711 up-regulated genes for male (M2), and 619 genes for female (F2)) involved in Gene Ontology enrichment analysis genes for male (M2), and 619 genes for female (F2)) involved in Gene Ontology enrichment analysis comparing to one-year-old fish (104 genes for male (M1), and 63 genes for female (F1)). DEGs were comparing to one-year-old fish (104 genes for male (M1), and 63 genes for female (F1)). DEGs were significantly enriched in several GO terms. In biological process, two-year-old male tongue sole (M2) significantly enriched in several GO terms. In biological process, two-year-old male tongue sole (M2) had a strikingly greater gene expression in reproduction (20 genes), metabolic process (406 genes), had a strikingly greater gene expression in reproduction (20 genes), metabolic process (406 genes), cellular process (502 genes), anatomical structure formation (78 genes) and cellular component organization (134 genes), while the highly expressed genes of female (F2) were mainly enriched on

Int. J. Mol. Sci. 2016, 17, 1402 5 of 17 cellular process (502 genes), anatomical structure formation (78 genes) and cellular component organization (134 genes), while the highly expressed genes of female (F2) were mainly enriched on multicellular organismal process (174 genes), localization (147 genes), establishment of localization (130 genes) and biological regulation (250 genes).

Table 1. The Gene ontology enrichment analysis of differential expressed genes. For Fisher’s exact test, p-value ≤ 0.05 is labeled as yellow, and p-value ≤ 0.01 is labeled as red.

M1 vs. F1 M2 vs. F2 GO Category GO Term Total No. of Genes M1 F1 M2 F2 GO:0005576 extracellular region 310 10 9 40 49 GO:0005623 cell 3238 69 38 425 400 GO:0019012 virion 11 3 0 5 2 GO:0031974 membrane-enclosed lumen 408 8 2 83 31 GO:0031975 envelope 105 7 0 22 18 GO:0032991 macromolecular complex 1014 34 26 175 151 Cellular Component GO:0043226 organelle 1669 35 28 282 212 GO:0044421 extracellular region part 214 3 4 34 33 GO:0044422 organelle part 1008 29 15 193 127 GO:0044423 virion part 11 3 0 5 2 GO:0044456 synapse part 75 3 1 3 23 GO:0044464 cell part 3238 69 38 425 400 GO:0045202 synapse 102 6 1 5 28 GO:0003824 catalytic activity 2105 34 13 298 210 GO:0005198 structural molecule activity 112 9 18 20 42 GO:0005215 transporter activity 393 19 5 30 68 GO:0005488 binding 2780 53 31 380 318 GO:0009055 electron carrier activity 6 0 0 1 1 GO:0015457 auxiliary transport protein activity 7 0 1 1 2 Molecular Function GO:0016209 antioxidant activity 14 0 0 1 2 GO:0030234 enzyme regulator activity 200 0 4 22 35 GO:0030528 transcription regulator activity 188 2 1 14 14 GO:0042056 chemoattractant activity 2 0 0 0 1 GO:0045182 translation regulator activity 26 1 0 8 2 GO:0045499 chemorepellent activity 1 0 0 0 0 GO:0060089 molecular transducer activity 430 3 2 19 35 GO:0000003 reproduction 73 0 0 20 5 GO:0001906 cell killing 3 0 0 0 1 GO:0002376 immune system process 189 2 1 28 26 GO:0008152 metabolic process 2756 46 37 406 297 GO:0008371 obsolete biological process 58 4 0 4 8 GO:0009987 cellular process 3553 71 48 502 403 GO:0010926 anatomical structure formation 378 8 8 78 43 GO:0016032 viral reproduction 30 1 1 8 8 GO:0016043 cellular component organization 652 15 8 134 77 GO:0016265 death 169 2 2 32 14 GO:0022414 reproductive process 72 1 1 19 10 Biological Process GO:0022610 biological adhesion 113 1 0 13 15 GO:0032501 multicellular organismal process 1315 34 17 151 174 GO:0032502 developmental process 1124 26 14 147 129 GO:0040007 growth 115 5 3 12 18 GO:0040011 locomotion 152 1 1 18 22 GO:0043473 pigmentation 1784 33 26 198 216 GO:0044085 cellular component biogenesis 327 11 22 75 58 GO:0048511 rhythmic process 11 0 0 0 1 GO:0050896 response to stimulus 606 19 9 81 83 GO:0051179 localization 955 30 11 120 147 GO:0051234 establishment of localization 790 30 10 100 130 GO:0051704 multi-organism process 55 2 1 11 11 GO:0065007 biological regulation 1927 38 29 219 250 All genes annotated by GO 5467 104 63 711 619

KEGG pathway enrichment analysis was also performed in Table S1B. Two-year-old male tongue sole had greater gene expression in genetic information processing, while female’s highly expressed genes were mainly enriched on organismal systems and human diseases pathway.

2.4. Genes with Sex-Biased Expression Potentially Associated with Growth As a vital mariculture fish, growth differences between male and female tongue sole are attracting more and more attention of researchers. Two-year-old female tongue sole are bigger in size and have Int. J. Mol. Sci. 2016, 17, 1402 6 of 17 higher growth rates than their male counterparts. Strikingly different gene expression patterns were also observed in the brain of the two sexes (Figure2). Gene Ontology is known to describe the properties of genes and their products in any organism. Based on GO terms, we attempted to identify sex-biased genes related with sexually dimorphic phenotypic traits. Here, we mainly focus on detecting the sex-biased genes for growth and reproduction associated with GO terms. According to GO annotation, 5467 genes were annotated by Gene Ontology. In biological process, 115 genes were assigned to growth (GO: 0040007) (Figure1 and Figure S1). Thirty-three of the genes were sexually differentially expressed, which are called potential growth-associated DEGs in this study (Figure1 and Table S3). In two-year-old tongue sole, 30 differentially expressed genes were assigned to growth (Table2), which accounted for 91% genes of potential growth-associated DEGs. The expression level of these genes in two development stages of tongue sole are plotted in Figure S2, and the significant analysis are listed in Table S3. Twelve genes were significantly highly expressed in M2 compared with F2 (Table2 and Table S3A), including h3f3b, hsc70, exosc9, vdac2, ppp2r1a, etc. These genes were only highly expressed in M2, with no significant differences in gene expression among M1, F1 and F2 (Table S3A). Another 18 genes were found to be down regulated in two-year-old males compared to the other three samples (Table2 and Table S3A), including mdk, gap43, ptn, gja1, ninj2, cxcl12b, fgf12, etc. These genes are mainly related to growth, fin regeneration and tissue regeneration. Significantly expressed DEGs were detected in all samples, but interestingly, most of these genes were only up or down regulated in M2 compared to the other samples.

2.5. Genes with Sex-Biased Expression Potentially Associated with Reproduction Reproduction of tongue sole is another important focus in this study. According to GO annotation, 73 genes were assigned to reproduction (GO: 0000003) in biological process (Figure1 and Figure S1). Twenty-five of them were differentially expressed between sexes, which were called potential reproduction-associated DEGs in this study (Table3). The expression level of these genes in two development stages of tongue sole is plotted in Figure S3, and the statistical test analysis is listed in Table S3. For two-year-old fish, 20 genes were found to be up-regulated genes in males, which accounted for the majority of sex-biased genes influencing in reproduction (Table3 and Table S3B). Those DEGs were only highly expressed in M2, and with no significant differences among the other three samples (Table S3B), which may be closely related to male development process. Nevertheless, only five genes were identified as female-biased genes (Table3), and these genes were found to be down regulated in M2 compared to F2 (Figure S3B).

2.6. qPCR Validation of RNA-Seq Results In order to validate the expression pattern of DEGs identiﬁed by RNA-Sequencing, we randomly selected eleven genes from DEGs potentially associated with growth or reproduction (Tables2 and3) for qPCR validation, including vdac2, ccnblip1, ropn1l, exosc9, cct7, mdk, ywhaq, gap43, cxcl12b, foxb1 and spin1. M2 was used as the reference in 2−∆∆Ct method to calculate the relative gene expression level. Comparing the relative expression level of eleven selected genes, most results of qPCR were consistent with the results of RNA-Seq (Figure3). The Pearson’s correlation of log 10(fold-change) between qPCR and RNA-Seq was 0.80, indicating the accuracy and reliability of RNA-Seq based transcriptome analysis. Int. J. Mol. Sci. 2016, 17, 1402 7 of 17

Table 2. Differentially expressed genes (DEGs) in two-year-old tongue sole potentially associated with growth.

FPKM p-Value Gene Annotation GO Function M2 F2 M2 vs. F2 DEGs Up Regulated in M2 h3f3b 670.6 193.2 1.9E-56 Histone H3.3 Positive regulation of cell growth (GO:0030307) hsc70 247.9 0.1 5.5E-34 Heat shock cognate 70 kDa protein Fin regeneration (GO:0031101) exosc9 164.6 13.2 1.7E-32 Exosome complex component RRP45 Positive regulation of cell growth (GO:0030307) vdac2 164.4 51.1 7.9E-14 Voltage-dependent anion-selective channel protein 2 Fin regeneration (GO:0031101) Serine/threonine-protein phosphatase 2A 65 kDa regulatory ppp2r1a 237.7 108.1 9.4E-11 Growth (GO:0040007) subunit A β isoform timm50 44.6 12.1 2.5E-05 Mitochondrial import inner membrane translocase subunit TIM50 Growth (GO:0040007) bmp2 30.6 6.1 5.3E-05 Bone morphogenetic protein 2 Growth (GO:0040007) ascl1 17.0 1.1 9.1E-05 Achaete-scute homolog 1 Sensory epithelium regeneration (GO:0070654) suv420h1 31.8 7.3 1.1E-04 Histone-lysine N-methyltransferase SUV420H1 Regulation of multicellular organism growth (GO:0040014) orc1 15.7 1.1 1.8E-04 Origin recognition complex subunit 1 Regulation of multicellular organism growth (GO:0040014) nenf 26.8 5.7 2.2E-04 Neudesin neurotrophic factor Growth (GO:0040007) dnajc2 42.6 16.0 9.6E-04 dnaJ homolog subfamily C member 2 Negative regulation of cell growth (GO:0030308) DEGs Down Regulated in M2 mdk 5.3 667.8 1.7E-157 Midkine Growth (GO:0040007) gap43 2.3 442.4 2.3E-100 Growth associated protein 43 Tissue regeneration (GO:0042246) ptn 30.3 287.1 3.1E-56 Pleiotrophin Growth (GO:0040007) gja1 1.9 222.0 6.1E-54 Gap junction α-1 protein Fin regeneration (GO:0031101) ninj2 55.5 255.5 1.1E-34 Ninjurin-2 Tissue regeneration (GO:0042246) cxcl12b 33.3 131.8 1.1E-16 Stromal cell-derived factor 1 precursor Fin regeneration (GO:0031101) fgf12 2.0 56.1 5.0E-15 Fibroblast growth factor 12 Growth (GO:0040007) gcfc2 23.4 102.5 2.3E-14 GC-rich sequence DNA-binding factor 2 Fin regeneration (GO:0031101) sox2 0.7 38.5 5.3E-11 Transcription factor SOX-2 Fin regeneration (GO:0031101) fyna 2.8 38.2 1.0E-09 Tyrosine-protein kinase fyna Fin regeneration (GO:0031101) epha4 1.7 34.5 1.9E-09 Ephrin type-A receptor 4 Negative regulation of collateral sprouting of intact axon in response to injury (GO:0048685) bdnf 1.9 29.3 6.6E-08 Brain-derived neurotrophic factor Growth (GO:0040007) cdh2 0.6 24.8 1.5E-07 cadherin-2-like Tissue regeneration (GO:0042246) rerg 3.0 29.9 2.6E-07 Ras-related and estrogen-regulated growth inhibitor Negative regulation of cell growth (GO:0030308) ctgf 2.5 22.9 9.4E-06 Connective tissue growth factor Regulation of cell growth (GO:0001558) igfbp1 0.2 17.9 9.8E-06 Insulin-like growth factor-binding protein 1 Regulation of cell growth (GO:0001558) klf6 2.6 22.5 1.3E-05 Krueppel-like factor 6 Organ growth (GO:0035265) sptbn1 7.0 27.5 1.7E-04 Spectrin β chain, non-erythrocytic 1 Positive regulation of multicellular organism growth (GO:0040018) Int. J. Mol. Sci. 2016, 17, 1402 8 of 17

Table 3. Differentially expressed genes (DEGs) in two-year-old tongue sole potentially associated with reproduction.

FPKM p-Value Gene Annotation GO Function M2 F2 M2 vs. F2 pleaDEGs Up Regulated in M2 ccnb1ip1 661.4 2.7 3.6E-138 E3 ubiquitin-protein ligase CCNB1IP1 Reproductive cellular process (GO:0048610) rsph1 516.7 5.7 1.4E-118 Radial spoke head 1 homolog Reproduction (GO:0000003) ropn1l 343.4 0.8 1.5E-66 Ropporin-1-like protein Spermatid development (GO:0007286) alkbh5 180.5 17.9 4.5E-33 RNA demethylase ALKBH5 Spermatogenesis (GO:0007283) henmt1 150.3 0.0 2.4E-29 Small RNA 2’-O-methyltransferase Oocyte development (GO:0048599) cct5 358.3 136.8 3.4E-21 Chaperonin containing T-complex polypeptide 5 Binding of sperm to zona pellucida (GO:0007339) ovol1 112.1 0.1 3.2E-19 Putative transcription factor Ovo-like 1 Spermatogenesis (GO:0007283) klhl10 54.7 0.0 7.0E-14 Kelch-like protein 10 Spermatid development (GO:0007286) cct7 329.3 153.7 1.4E-13 Cct7 protein Binding of sperm to zona pellucida (GO:0007339) cct4 305.8 147.9 8.8E-12 Cct4 protein Binding of sperm to zona pellucida (GO:0007339) fem1b 44.6 3.0 2.5E-10 Protein fem-1 homolog B-like Epithelial cell maturation involved in prostate gland development (GO:0060743) sf1 103.4 33.7 9.2E-09 Splicing factor 1 Leydig cell differentiation (GO:0033327) styx 69.8 20.2 3.6E-07 Serine/threonine/tyrosine-interacting protein Spermatogenesis (GO:0007283) Positive regulation of cortical granule exocytosis by elevation of cytosolic calcium ptbp1 45.3 9.4 1.2E-06 Polypyrimidine tract-binding protein 1-like ion concentration (GO:0060472) tbp 41.8 9.0 4.4E-06 TATA box binding protein Spermatogenesis (GO:0007283) pld6 24.9 2.6 1.1E-05 Phospholipase D family member 6 P granule organization (GO:0030719) polr2h 50.9 15.8 3.2E-05 DNA-directed RNA polymerases I%2C II%2C and III subunit RPABC3 Positive regulation of viral transcription (GO:0050434) pacrg 38.8 10.5 7.8E-05 Parkin coregulated gene protein Spermatid development (GO:0007286) tceb1 137.6 75.3 1.2E-04 Transcription elongation factor B polypeptide 1 Positive regulation of viral transcription (GO:0050434) tdrd9 13.3 0.6 2.9E-04 Putative ATP-dependent RNA helicase TDRD9 Fertilization (GO:0009566); DNA methylation during gametogenesis (GO:0043046) DEGs Down Regulated in M2 ywhaq 63.5 229.4 1.1E-25 YWHAQ protein Germarium-derived oocyte fate determination (GO:0007294) cxcl12b 33.3 131.8 1.1E-16 Stromal cell-derived factor 1-like Germ cell migration (GO:0008354) spin1 12.4 44.6 4.0E-06 Spindlin-1-like Gamete generation (GO:0007276) stau2 41.7 80.2 1.1E-04 Double-stranded RNA-binding protein Staufen homolog 2 Germ cell migration (GO:0008354) sptbn1 7.0 27.5 1.7E-04 Spectrin β chain, non-erythrocytic 1 Fertilization (GO:0009566) Int. J. Mol. Sci. 2016, 17, 1402 9 of 17 Int. J. Mol. Sci. 2016, 17, 1402 9 of 17

(A)

(B)

Figure 3. Brain transcriptome validation by qPCR using eleven selected genes: (A) Gene relative Figure 3. Brain transcriptome validation by qPCR using eleven selected genes: (A) Gene relative expressionexpression in in qPCR qPCR where where Error Error bars bars represent st standardandard deviation of of technical replicates replicates and and the the expressionexpression differences differences between between M2 M2 and and F2 F2 were were tested tested by by two-tailed Student’s Student’s tt-test,-test, with with 95% 95% confidenceconﬁdence level ( p < 0.05) 0.05) being being labeled labeled with with an an asterisk; asterisk; and and ( (BB)) gene gene expression expression in in RNA-Seq. RNA-Seq.

3. Discussion 3. Discussion This study conducted a transcriptome analysis of male and female brain tissues thereby This study conducted a transcriptome analysis of male and female brain tissues thereby providing providing the first assessment of the molecular mechanism underlying the reproductive the ﬁrst assessment of the molecular mechanism underlying the reproductive development of tongue development of tongue sole. We identified sex-biased genes and investigated up/down regulated sole. We identiﬁed sex-biased genes and investigated up/down regulated DEGs with respect to two DEGs with respect to two phenotypic traits (growth and reproduction). Finally, we validated eleven phenotypic traits (growth and reproduction). Finally, we validated eleven randomly selected potential randomly selected potential growth or reproduction associated DEGs by qPCR, thereby supporting growth or reproduction associated DEGs by qPCR, thereby supporting the reliability and accuracy of the reliability and accuracy of our transcriptome analysis. our transcriptome analysis.

3.1.3.1. The The Brain Brain Transcriptome Transcriptome of Tongue Sole BrainBrain transcriptome analysis analysis was was conducted conducted on on male and female tongue sole. The The reason reason we we chosechose one- one- and two-year-old individuals was was two-fold. Firstly, Firstly, males males and and females have significant significant differencesdifferences in thethe ageage ofof maturitymaturity and and body body weight. weight Early. Early sexual sexual maturation maturation of malesof males was was found found at the at theage age of nine of nine months, months, while while 21-month-old 21-month-old females females were stillwere immature still immature [25]. The [25]. body The weight body ofweight females of femaleswas 3.28 was times 3.28 higher times than higher males than at 21males months at 21 [25 months]. We tried [25]. to We capture tried to the capture transcriptome the transcriptome differences differencesbetween males between and femalesmales and at afemales stage withat a stage phenotypic with phenotypic divergence. divergence. Secondly, Secondly, we looked we for looked genes forthat genes contribute that tocontribute sexual dimorphism, to sexual dimorphism including upstream, including genes upstream activity thatgenes might activity contribute that might to sex contributedetermination to sex as determination well. We chose as one-well.and We two-year-oldchose one- and tongue two-year-old sole for tongue this research. sole for Two-year-oldthis research. Two-year-oldmales were mature, males whilewere femalesmature, werewhile still females immature. were still The stageimmature. selection The wasstage appropriate selection was and appropriateeffective to characterizeand effective theto characte sex-relatedrize transcriptomicthe sex-related transcriptomic expression profiles expression of tongue profiles sole, of since tongue we sole,identified since awe batch identified of differentially a batch of expresseddifferentiall genesy expressed in our assembled genes in our sequences. assembled sequences.

Int. J. Mol. Sci. 2016, 17, 1402 10 of 17

3.2. Male and Female Brain Expression Pattern Brain plays a central role in coordinating sexual function in mammals, and has remarkable plasticity in teleost [28]. Our results identified more genes to be over expressed in males than females, which is consistent with the findings on Manousaki’s work [20] on sharpsnout seabream, in which the authors identified a seven-fold increase of DEGs in two-year-old fish compared to one-year-old fish. More DEGs were detected in male tongue sole than female during two stages in our study.

3.3. Sexually Differentially Expressed Genes Potentially Associated with Growth A number of genes involved in growth were found to be down regulated in two-year-old male brains. These included mdk, which encodes a member of a small family of secreted growth factors that binds heparin and promotes cell growth [29–31], migration, and angiogenesis [32,33]. It was also reported as a retinoic acid-responsive gene concerned with prenatal development and neuritis growth [34]. In mouse and human embryogenesis, mdk is widely expressed during mid gestation, but expression becomes undetectable in later stages [35,36]. In the brain of adult mice and rats, expression of mdk is reduced to undetectable levels [37]. ptn, often studied together with mdk, is a secreted growth factor that induces neurite outgrowth [38–40]. It is also claimed to play essential roles in female reproduction in mice [41]. One of these two genes deﬁcient in mice will result in abnormal reproduction and development [41]. In rodents, these growth factors are highly expressed in early life and decrease to undetectable levels by adulthood in multiple organs [42]. gap43, a growth associated gene [43], plays a key role in nervous system [44] and it is related to nerve development, regeneration, and outgrowth. ninj2 is known to play a role in nerve regeneration and in the formation and function of other tissues [45–47]. In this study, the decreased expression level of these genes in M2 might be related to the maturation of male in this stage with growth retardation. However, these genes keep a certain level during two stages in female while it was still growing, which indicated that they might be essential for female growth. The up regulated genes potentially associated with growth in M2 included h3f3b, which is a replacement histone subtype in active genes [48], involved in DNA damage and cell cycle regulation [49,50]. exosc9 encodes a component of the exosome complex with RNA degradation function [51], which prevents premature differentiation and promotes self-renewal by maintaining a low mRNA level of transcription factor grhl3 [52]. These two genes both have a positive regulatory effect of cell growth. The expression level of h3f3b in two-year-old male (M2) was two times higher than other samples, and exosc9 also shows strikingly higher expression level in two-year-old males (M2), which further suggests an enhanced rate for cell cycle regulation and enhanced self-renewal in the brain of male tongue sole.

3.4. Sexually Differentially Expressed Genes Potentially Associated with Reproduction A few genes potentially associated with reproduction are discussed as follows. ccnb1ip1, also called as hei10, is a member of the E3 ubiquitin ligase family that acts as a limiting factor for crossing-over during meiosis [53] and involved in male gametogenesis and plays a role in cell cycle regulation [53,54]. When cells enter into mitosis, ccnb1ip1 may interact with Cyclin B1 directly to control protein degradation in human [55], indicating its function of inhibiting cell growth. ropn1l encodes a sperm protein of the ropporin family, which interacts with Protein Kinase A to regulate glycogen, sugar, and lipid metabolism [56]. Ropporin had been identified as a spermatogenic cell protein, but also has weak expression in normal non-testis tissues in latest studies, including brain tissue [57]. In Tonevitsky’s study [58], ropn1l had an increasing expression level in blood during the relaxation time after 30 min exercise of tested athletes. ropn1l was highly expressed in two-year-old male (M2), indicating its potential function in maturity male tongue sole. cct4, cct5 and cct7 are members of the chaperonin containing TCP1 complex (CCT), act as a molecular chaperone to assist the folding of proteins upon ATP hydrolysis [40,59,60], which are involved in binding of spermatozoa to Int. J. Mol. Sci. 2016, 17, 1402 11 of 17 the zona pellucida. The CCT complex is a large multi-subunit complex that assists the folding of a variety of proteins, including several tubulin and actin proteins [61,62] and it plays a key role in cell cycle regulation, cytoskeleton assembly and cell division [61]. Grantham [61] indicated that full CCT activity is essential for normal cell growth and division in mammalian cell. The functional significance of the increased cct4, cct5 and cct7 expression was unclear, but may have a possible relationship with the quicker maturation in males compared to females. Other genes found in our research that might have significance but still unknown roles in the brain associated with growth and reproduction. Despite the relatively low number, these genes may become biological significant when interacting with the other genes in functional gene networks controlling and maintaining reproduction and development of tongue sole.

4. Materials and Methods

4.1. Experimental Fish and Sample Collection All procedures involving sample handling and treatment used in this study were approved by the Animal Care and Use Committee at Heilongjiang River Fisheries Research Institute (ACUC-HRFRI). All experiments were conducted in accordance with the relevant guidelines and regulations. The fish used in this study included 20 male tongue sole (10 one-year-old juveniles and 10 two-year-old adults) and 20 female tongue sole (10 one-year-old juveniles and 10 two-year-old adults). The average body weights of one-year-old males and females were 54 and 99 g, and the average body lengths were 21 and 25 cm, respectively. For two-year-old fish, the average weights were 337 and 1380 g, and average lengths were 27 and 42 cm, for males and females, respectively. Females were much bigger than males. Two-year-old females were still immature, while males were mature. All forty fish came from one full-sib family in National Fish Original Species Farm at Tianjin, China. One-year-old fish were collected on 10 August 2013 and two-year-old on 12 August 2014. The sex of the fish was confirmed anatomically. Tissues of the whole brain from one- and two-year-old fish were collected and stored in 1.5 mL RNAlater tube (QIAGEN, Hilden, Germany), and then stored at −80 ◦C freezer for subsequent RNA extraction.

4.2. RNA Isolation Brain samples were taken out of the −80 ◦C freezer and homogenerated with a TissueRuptor (QIAGEN) to a fine solution and then treated with RNase free DNase I (QIAGEN) for high RNA quality and yield. Total RNA were extracted from each sample using the RNeasy Lipid Tissue Kit (QIAGEN) according to the manufacturer’s instructions. The quality and quantity of RNA were examined by Thermo ScientificTM NanoDropTM 8000 Spectrophotometer (Thermo Scientific, Wilmington, DE, USA) and Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Only RNA with OD260/280 ≥ 1.8 and RNA integrity number (RIN) ≥ 7 was stored for the following library construction and sequencing. Equal quantities of high quality RNA from each brain sample were pooled together for subsequent cDNA synthesis and sequencing.

4.3. cDNA Library Construction and Illumina Sequencing Four RNA-Seq libraries were prepared and sequenced by BerryGenomics sequencing company (Beijing, China). cDNA library was constructed following the protocol of Illumina TrueSeq RNA Sample Prep Kit (Illumina, San Diego, CA, USA). The library was sequenced using Illumina HiSeq 2000 platform. In total, 100 bp paired-end reads with an insert size of 330 were obtained. The clean reads from the four transcriptomes were obtained by ﬁltering out low quality reads (reads with quality value of ≤20) and adaptor-only reads from the raw data. Int. J. Mol. Sci. 2016, 17, 1402 12 of 17

4.4. Sequence Assembly and Analysis The quality control of RNA-Seq data was conducted by NGS QC Toolkit [63] with default parameters. Clean paired-end reads were aligned to the genome of tongue sole [2] using TopHat [64]. Then the mapping ﬁles were analyzed using Cufﬂinks [65] to assemble the reads into transcripts for each dataset. Complete transcripts were obtained by merging the assemblies of all datasets using Cuffmerge. Duplicate sequences were removed by cd-hit [66].

4.5. Functional Annotation and Ontology All expressed genes were aligned to NCBI non-redundant (NR) protein database by using BLASTP with E-value < 1 × 10−5. With the result of BLASTP, Gene ontology (GO) [67] annotation was performed using Blast2GO [68]. The top two GO terms associated with transcripts were retrieved, and then the annotation genes were grouped into three categories, biological process, molecular function, and cellular components. Genes annotated on growth (GO: 0040007: BP) and reproduction (GO: 0000003: BP) were selected as potential growth- and reproduction-associated genes, respectively. Pathways from Kyoto Encyclopedia of Genes and Genomes (KEGG) [69] were assigned with differential expressed genes by using the online KEGG Automatic Annotation Server (KAAS) [70].

4.6. Identification of Differentially Expressed Genes (DEGs) and Pathway Enrichment Analysis FPKM (Fragments Per Kilobase of exon per Million fragments mapped reads) is widely used in RNA-Sequencing to represent the gene expression level [71]. The FPKM is calculated by Cuffdiff [72] method. Then, DEGseq [73] was used to identify sexually differentially expressed genes (DEGs) based on the MARS model (MA-plot-based method with Random Sampling model). Genes with “p-value < 0.001” were selected as DEGs. False discovery rate (FDR) was widely set at 0.05 to determine the threshold for the p-value. Sex-biased genes were strictly identified from DEGs with at least 2-fold difference between genders (|log2(FRKM_ZZ/FPKM_ZW)| ≥ 1). Genes meeting “FPKM_ZZ < 2 and FPKM_ZW < 2” statistical criteria were grouped as non-expressed genes (NEGs). All remaining genes were classified as co-expressed genes (CEGs). This way, all transcribed genes were classified into three groups: DEGs, CEGs and NEGs. Fisher’s exact test was conducted to further detect functional DEGs for RNA-Seq data [74,75]. The right-tailed Fisher’s exact test was used to identify the enriched GO terms or KEGG categories. All transcribed genes were divided into two sets, differentially expressed genes (DEGs) and non-DEGs. Fisher’s exact test was calculated based on a 2 × 2 contingency table (Table4). The two columns of the table were separated by DEGs and non-DEGs. The two rows were separated by the given category A and other categories. The Fisher’s exact test p-value for each category was calculated in the following formula.

Ca Cc (a + b)! (c + d)! (a + c)! (b + d)! p = a+b c+d = a+c (a + b + c + d) a b c d Ca+b+c+d ! ! ! ! !

p-Value ≤ 0.05 were selected as a threshold to determine the signiﬁcant enriched GO terms or KEGG pathways.

Table 4. 2 × 2 contingency table for Fisher’s exact test.

Gene Annotation DEGs Non-DEGs All Transcribed Genes Category A a b a + b Other categories c d c + d All categories a + c b + d a + b + c + d “a” represented the No. of DEGs annotated on category A; “b” represented the No. of non-DEGs annotated on category A; “c” represented the No. of DEGs annotated on the other categories except category A; and “d” represented the No. of non-DEGs annotated on the other categories except category A. Int. J. Mol. Sci. 2016, 17, 1402 13 of 17

4.7. Experimental Validation by qPCR Sexually differentially expressed genes were validated using quantitative real-time PCR (qPCR). Brain samples were dissected from three male and three female tongue sole at both one and two years of age. Total RNA was extracted from each brain sample and reverse-transcribed using MMLV reverse transcriptase (Invitrogen, Carlsbad, CA, USA). Primers used in qPCR were designed with the help of Primer Premier 6.0. Quantitative real-time PCR was performed using the SYBR Green I Master Mix (TaKaRa, Dalian, China) in Applied Biosystems Prism 7500-fast real-time PCR system. The PCR reaction conditions were as follows: 95 ◦C for 5 min, followed by 40 amplification cycles of 95 ◦C for 15 s and 60 ◦C for 30 s. β-Actin had been validated as a useful internal control for gene expression studies using quantitative real-time PCR in tongue sole [24,76], and was used as the reference gene to normalize the mRNA expression levels of all the validated genes in this study. The sequence of beta-actin gene and primers used in this study were referred from Chen’s study [2]. The fold change of each gene was calculated by the relative quantification (2−∆∆Ct) method [77]. qPCR analysis was repeated three times to confirm gene expression patterns. Expression differences between samples were tested by two-tailed Student’s t-test, and 95% confidence level (p < 0.05) was selected to determine the differentially expressed genes.

5. Conclusions In this study, we performed a comprehensive analysis of the transcriptome of one- and two-year-old male and female brains of Cynoglossus semilaevis by high-throughput Illumina sequencing. A total of 21,475 unigenes were obtained by transcriptome analysis. Differential expression analysis combined with gene enrichment analysis revealed a number of potential growth and reproduction associated genes. Most of these genes are only up or down regulated in two-year-old males, and had no signiﬁcant differences in expression among one-year-old males and females and two-year-old females. Potential growth and reproduction associated genes in our work might be the candidate factors affecting sexual dimorphism in tongue sole, laying the foundation to understand the complex process of development and sex determination of this economic valuable species.

Supplementary Materials: Supplementary materials can be found at www.mdpi.com/1422-0067/17/9/1402/s1. Acknowledgments: We thank Xiaofeng Zhang, Shuqun Xue, and Qiushi Wang for their good suggestion on this manuscript. This research was supported by grants from the Taishan Scholar Leading Talent Team Support Program for Blue Industry of Shandong Province, National Science Foundation of China (31302177), Heilongjiang River Fisheries Research Institute Foundation (HSY201505), and National Science Foundation of Heilongjiang Province (LC201419). Author Contributions: Xiaowen Sun and Jianguo Lu designed the experiments. Pingping Wang analyzed the data. Min Zheng performed the experiments. Jian Liu and Yongzhuang Liu contributed reagents and materials. Pingping Wang and Jianguo Lu wrote and edited the paper. Conﬂicts of Interest: The authors declare no conﬂict of interest. The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.

Abbreviations

GO Gene Ontology DEG Differentially Expressed Gene NEG Non-Expressed Gene CEG Co-Expressed Gene FPKM Fragments Per Kilobase of exon per Million fragments mapped reads qPCR quantitative real-time PCR

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